Access to Education in Bangladesh: Country Analytic Review of Primary and Secondary Education

This country analytical review examines the key issues in access to and participation in primary and secondary education in Bangladesh, with a special focus on areas and dimensions of exclusion. Against a background of overall progress, particularly in closing the gender gap in primary and secondary enrollment, the research applies a conceptual framework outlining different forms of exclusion and presents two significant findings which compromise access and diminish gains made: high dropout rates at primary and secondary levels and nominal access but virtual exclusion from quality learning. Other areas surveyed in the review include interventions by public sector and non-governmental providers in primary and secondary education as well as the financing of basic education. This review of the literature concludes with suggestions for future research directions that might lead to new understanding and insights on equitable access and participation

Response Of The Dupi Tila Aquifer to intensive pumping in Dhaka, Bangladesh

This paper focuses on the water-quantity issues facing Dhaka because of the rapid exploitation of the Dupi Tila aquifer. Dhaka is one of the world’s largest groundwater-dependent cities, relying on water withdrawn from this underlying semiconfined sand aquifer. A meteoric rise in well construction in both the private and public sectors in recent years has produced an estimated 1,300 boreholes that tap the aquifer in urban and suburban parts of the city. Analysis of construction records for public-supply wells drilled between 1970 and 2000 shows that water levels are falling in several areas of the city despite apparently favorable recharge conditions . The productivity of boreholes as measured by specific capacity has also declined significantly. Even though the aquifer system is vital to the infrastructure of the city it remains a poorly quantified resource, and until this is resolved by investment in evaluation studies, attempts to efficiently manage the resource in a sustainable way will be frustrated

Acoustic data optimisation for seabed mapping with visual and computational data mining

Oceans cover 70% of Earth’s surface but little is known about their waters. While the echosounders, often used for exploration of our oceans, have developed at a tremendous rate since the WWII, the methods used to analyse and interpret the data still remain the same. These methods are inefficient, time consuming, and often costly in dealing with the large data that modern echosounders produce. This PhD project will examine the complexity of the de facto seabed mapping technique by exploring and analysing acoustic data with a combination of data mining and visual analytic methods. First we test the redundancy issues in multibeam echosounder (MBES) data by using the component plane visualisation of a Self Organising Map (SOM). A total of 16 visual groups were identified among the 132 statistical data descriptors. The optimised MBES dataset had 35 attributes from 16 visual groups and represented a 73% reduction in data dimensionality. A combined Principal Component Analysis (PCA) + k-means was used to cluster both the datasets. The cluster results were visually compared as well as internally validated using four different internal validation methods. Next we tested two novel approaches in singlebeam echosounder (SBES) data processing and clustering – using visual exploration for outlier detection and direct clustering of time series echo returns. Visual exploration identified further outliers the automatic procedure was not able to find. The SBES data were then clustered directly. The internal validation indices suggested the optimal number of clusters to be three. This is consistent with the assumption that the SBES time series represented the subsurface classes of the seabed. Next the SBES data were joined with the corresponding MBES data based on identification of the closest locations between MBES and SBES. Two algorithms, PCA + k-means and fuzzy c-means were tested and results visualised. From visual comparison, the cluster boundary appeared to have better definitions when compared to the clustered MBES data only. The results seem to indicate that adding SBES did in fact improve the boundary definitions. Next the cluster results from the analysis chapters were validated against ground truth data using a confusion matrix and kappa coefficients. For MBES, the classes derived from optimised data yielded better accuracy compared to that of the original data. For SBES, direct clustering was able to provide a relatively reliable overview of the underlying classes in survey area. The combined MBES + SBES data provided by far the best accuracy for mapping with almost a 10% increase in overall accuracy compared to that of the original MBES data. The results proved to be promising in optimising the acoustic data and improving the quality of seabed mapping. Furthermore, these approaches have the potential of significant time and cost saving in the seabed mapping process. Finally some future directions are recommended for the findings of this research project with the consideration that this could contribute to further development of seabed mapping problems at mapping agencies worldwide

Remote Sensing of Sun-Induced Chlorophyll Fluorescence for Advanced Ecosystem Evapotranspiration Estimates

A precise ecosystem evapotranspiration (ET) estimate is essential for understanding the complex relationship between plants' energy-water-carbon fluxes. Besides, robust ecosystem ET estimation under different water stresses can provide insight into plants' response to extreme weather and environmental conditions. However, for such very preciseness, we must accept the individual and comprehensive interlinked mechanistic relationships between ecosystem ET and its controlling variables for determining the response of ecosystem ET towards extreme climate events. Due to recent drought events in the European continent since the 2000s, many geographical hotspots are getting attention to understanding the complicated mechanistic relationship between ecosystem ET and its controlling variables under such extreme water stress conditions. Consequently, precise ecosystem ET estimation of the European continent's water-stressed ecosystems, i.e. agriculture, will give insight into the sustainability of Europe's agricultural production to ensure sufficient food for millions of people in future. The recent heatwaves and drought in 2018 impacted ecosystem ET substantially over the European continent, which may be a big concern for the European ecosystems' future water, energy, and CO2 balance. The research outcomes of the first research article (c.f. Ahmed et al., 2021) showed that the European continent had up to 50% reduced ecosystem ET compared to a 10-year reference period due to a combined heatwave and drought event in 2018. The results also showed extreme surface air temperature (Tsa) and precipitation (P) anomalies. Due to such extreme climatic phenomena, agricultural land, mixed natural vegetation, and the European continent's non-irrigated agricultural areas were mainly affected. In conclusion, the first research article explains the importance of modelling precise ecosystem ET in variable time and space. However, modelling and estimating precise ecosystem ET is still challenging, especially under extreme climates within continuous time and ample variable space. Remote sensing (RS) data based modelling approaches often encounter uncertainties due to complex parameterizations of different variables for ecosystem ET modelling schemes. Further, uncertainties may be introduced by different data types, data quality, multi-sensor systems, and spatio-temporal resolution of satellite images. The growing advancement of using RS based sun-induced chlorophyll fluorescence (SIF) for ecosystem studies has introduced SIF's use case for ecosystem ET estimates. However, previous studies have limitations due to applying specific ET models, only considering energy or water constraints and different strategies to add SIF in such specifically selected models. The second research article (c.f. Ahmed et al., 2023) investigated possible SIF integration in an advanced ecosystem ET modelling scheme. The research considers the mechanistic relationships between SIF and ecosystem ET and their abiotic and biotic drivers. The results concluded the best possible ways of empirically applying SIF for ecosystem ET estimates under water-limited and well-watered conditions under an experimental setup in maize crop fields in northern Italy. The research assesses the absolute and relative sensitivity of several SIF based ecosystem ET estimation strategies for evolving soil water limitation using extensive in-situ and airborne RS data acquired during the water limitation experiment. The study evaluated five strategies to integrate SIF in an ecosystem ET modelling framework based on the Penman Monteith (PM) and the Ball-Berry-Leuning (BBL) models. The results showed that replacing canopy conductance (including canopy resistance and leaf's net CO2 assimilation rate), leaf area index and net radiation with SIF significantly correspond with in-situ reference ecosystem ET (unit based conversion of measured sap flow) under evolving water limitation. Indeed, considering a single SIF as an indirect proxy for ecosystem ET with a one-to-one relationship showed inconsequential outcomes. In conclusion, the research's outcomes give insight into the importance and scientific advantage of applying SIF in a multi-sensors RS data based framework to increase the sensitivity of SIF based ecosystem ET estimates for evolving water limitations. Besides, the results highlighted the uses of SIF for the scientific advancement of ecosystem drought monitoring. Recent studies have proposed the usability of SIF to establish SIF-based drought indices (DIs) using comparatively coarse spatio-temporal resolution RS data. However, the temporal and spatial sensitivity of such newly proposed SIF-based DIs for growing crop water limitation with higher spatio-temporal resolution RS data must be determined. Therefore, the third Ph.D. research article (in review) conducted a temporal and spatial sensitivity analysis of SIF-based DI for gradually increasing soil and crop water limitation for different crop types. Temporal sensitivity analysis of the study showed that SIF based DI is sensitive throughout evolving soil water limitations, and traditional optical index (OI) based DI is only sensitive at extreme soil water limitations. However, both DIs showed their sensitivity towards the highest soil water limitation. Spatial sensitivity analysis reveals that SIF based DI is sensitive towards decreasing plant available water (PAW) zones and continues till the lowest PAW zones, and OI based DI is only sensitive in the lowest PAW zones. Furthermore, like the temporal analysis, from the spatial analysis, it is also visible that both DIs are sensitive towards the lowest PAW. The research concludes that both SIF based and traditional OI based DIs are sensitive to increasing soil and crop water limitation; however, the experimental setup was not sufficient to say that SIF based DI can be more beneficial for monitoring crop water limitation throughout drought events than OI based DI, instead, both DIs can be applied for monitoring evolving soil and crop water limitation within shorter spatio-temporal scales. Besides, SIF based DI can be applicable for predicting early crop water limitation and promoting incentive preparation for drought, but further studies within different ecosystems with different environmental conditions are needed. In contrast, resulting ecosystem ET values and SIF have been examined with their absolute, relative, temporal, and spatial sensitivities under different soil and crop water availability for monitoring and predicting early plants’ water limitation within different spatio-temporal scales in various spaces and times. Combining all three research articles gives a forward consideration towards the sensitivity of SIF for robust forward ecosystem ET modelling and SIF embedded drought monitoring application within an advanced multi-sensors RS data modelling approach

A Study on Vegetable Export for the Economic Development of Bangladesh and Its Entrepreneurial Opportunities for Young Educated Bangladesh People

This study tries to explain the prevailing vegetable supply chain system in Bangladesh which impact on International Market linkages includes some markets, number of intermediaries, and involvement of Stakeholder. Next, it shows many limitations within the present supply chain where the issues of export of vegetable supply chain have discoursed thoroughly. Then, the influences of lack of effective supply chain linkages are discussed. The main difficulties met by the growers, Exporter, and negotiators were deficiency of money, Training, production, Packaging Knowledge, poor communication and transport services, lack of adequate storage services, lack of suitable market info, higher market tolls, deficiency of market facilities, etc. The growers and intermediaries also suggested some solutions to those difficulties. As vegetables are perishable products, the study provides an overview of the issues and solutions within the use of cargo space at the airport. The govt should take the required steps to undo these problems and thus extend the effectiveness of vegetable supply chain export marketing in Bangladesh. Here shows a proposed vegetable supply chain and policy level suggestion for International Market linkages. At present Bangladesh is in the demographic dividend. It includes a large number of educated unemployed.  This study provides a detailed explanation of how to start a new business to grow as an entrepreneur.  These people can play a significant role in the country's GDP by exporting vegetables from the country by obtaining export licenses and earning foreign exchange. DOI: 10.7176/RHSS/11-20-09 Publication date:October 31st 2021

The impact of the farm economic crisis on the career aspirations of Iowa farm youth

The impact of the farm economic crisis on the career aspiration of the Iowa farm-reared undergraduate students of Iowa State University is examined. More than half of the sample studied reported that the crisis has affected their career plans to some extent. A selected number of variables, background and attitudinal in nature, were examined to predict the students\u27 alternative career choices. A path model was formulated and tested. The LISREL computer program was used to estimate and test several versions of the model. Results show that parents\u27 economic status, son\u27s ideological commitment to agricultural, and his assessment of the farm crisis, among other variables, are the most significantly important variables that explain students\u27 alternative and realistic career choices

Effects of high salt load on renal Hemodynamics and function in Normotension and hypertension: role of Alpha 1-adrenoceptor.

Hipertensi merupakan penyebab utama morbiditi dan kematian yang berkait rapat dengan penyakit jantung koroner, kegagalan ginjal dan strok. Natrium memainkan peranan patofisiologi yang penting di dalam pembentukkan hipertensi. Hypertension is a major cause of coronary heart disease, renal failure and stroke. Sodium plays an important pathophysiological role in the development of hypertension

POLICY-BASED MIDDLEWARE FOR MOBILE CLOUD COMPUTING

Mobile devices are the dominant interface for interacting with online services as well as an efficient platform for cloud data consumption. Cloud computing allows the delivery of applications/functionalities as services over the internet and provides the software/hardware infrastructure to host these services in a scalable manner. In mobile cloud computing, the apps running on the mobile device use cloud hosted services to overcome resource constraints of the host device. This approach allows mobile devices to outsource the resource-consuming tasks. Furthermore, as the number of devices owned by a single user increases, there is the growing demand for cross-platform application deployment to ensure a consistent user experience. However, the mobile devices communicate through unstable wireless networks, to access the data and services hosted in the cloud. The major challenges that mobile clients face when accessing services hosted in the cloud, are network latency and synchronization of data. To address the above mentioned challenges, this research proposed an architecture which introduced a policy-based middleware that supports user to access cloud hosted digital assets and services via an application across multiple mobile devices in a seamless manner. The major contribution of this thesis is identifying different information, used to configure the behavior of the middleware towards reliable and consistent communication among mobile clients and the cloud hosted services. Finally, the advantages of the using policy-based middleware architecture are illustrated by experiments conducted on a proof-of-concept prototype